Instructions to use NO8D/FaceControl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/FaceControl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("NO8D/FaceControl") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8572657271f53bc608fe44dab35dfcf9ec15408f27d4f1e060dfe9afea13d990
- Size of remote file:
- 41.4 MB
- SHA256:
- df3e5b352a46b74faba6de9c2d77b766168a8481b86b97d3c9b4849f1eb12923
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